“Enhancing Remote Learning Experiences with AI-Powered Adaptive Content Delivery Over Wireless Networks”

With the rise of remote learning, the demand for personalized learning experiences has significantly increased. This study designs and simulates an AI-powered adaptive content delivery system that utilizes Long Short-Term Memory (LSTM) networks to analyze students' learning progress and dynamically adjust the content. The system ensures real-time content transmission through wireless networks, particularly 5G technology. Experimental results demonstrate that the adaptive system significantly outperforms traditional fixed content systems in terms of improving student engagement, learning efficiency, and personalization of learning paths. The study also analyzes the system's performance under different network conditions, highlighting its scalability in large-scale applications. The findings suggest that AI technologies combined with advanced wireless networks can enhance the remote learning experience, with future work focused on further optimizing system performance and expanding data types to improve content personalization and real-time feedback.